Comments (1)
BatchNormalization
and Dropout
are lost in the process of model optimization; you can transcribe the weights yourself to the model structure defined in Keras.
from onnx2tf.
Related Issues (20)
- Conversion of YoloV5, conversion of StridedSlice from 5d to 4d HOT 7
- Failed to convert Real-ESRGAN x4-general (NCHW) HOT 1
- Error when onnx2tf: Floating point exception (core dumped) HOT 10
- Full int8 quantized model doesn't work when "flatc" is installed on the system HOT 8
- ValueError: Exception encountered when calling layer "tf.math.multiply_46" (type TFOpLambda).
- Facing onnx2tf converstion issue with resnet model mentioned in README HOT 1
- pre_explicit_broadcast should not expend scalar tensor HOT 13
- "GEMM: Dimension mismatch" during value validation phase HOT 4
- Exclude selected operations from INT8 quantized model HOT 18
- ValueError in MaxPool Layer during ONNX to TensorFlow Conversion with 3D Input HOT 5
- The tflite detection result converted from the yolo NAS model is inaccurate. HOT 5
- Converting quantized onnx with Q/DQ representation to full int8 TFLite model HOT 2
- Unable to replace flatten HOT 4
- How to convert onnx(NCHW) to NHWC and write back to onnx file Because my HW takes onnx file as input in NHWC format HOT 3
- How to convert onnx(NCHW) to NHWC(without adding transpose) and write back to onnx file HOT 1
- How to convert onnx(NCHW) to NHWC(without adding transpose) and write back to onnx file HOT 3
- Please do reply for the last time either this issue or @ How to convert onnx(NCHW) to NHWC(without adding transpose) and write back to onnx file #586 HOT 1
- ONNX Split operation converts to a tf StridedSlice operation with outputs in the wrong order. HOT 2
- Depth_Anything to ONNX model's conversion failed HOT 1
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